Abstract
This paper presents an overview of the work under development within MAESTRI EU-funded collaborative project. The MAESTRI Total Efficiency Framework (MTEF) aims to advance the sustainability of manufacturing and process industries by providing a management system in the form of a flexible and scalable platform and methodology. The MTEF is based on four pillars: (a) an effective management system targeted at process continuous improvement; (b) Efficiency assessment tools to support improvements, optimisation strategies and decision support; (c) Industrial Symbiosis paradigm to gain value from waste and energy exchange; (d) an Internet-of-Things infrastructure to support easy integration and data exchange among shop-floor, business systems and tools.

Abstract
For a company it is important to improve resource and eco-efficiency in order to save money, the environment and to improve the company's image. We present a new approach combining Multi-layer Stream Mapping (MSM) and a Business Process Based Monitoring and Control Framework to monitor relevant process variables and use the values as an input for MSM to reduce waste and costs. This combination supports the decision making process and allows to identify major inefficiencies and provides means for more sustainability.

Abstract
The overall aim of the Efficiency Framework is to encourage a culture of continuous improvement and sustainability within manufacturing and process industries. The framework presented supports informed decision-making processes and helps to define strategies for continuous performance improvement. The proposed innovative Efficiency Framework, materialized through the integration of concepts and results provided by eco-efficiency methodology, namely Eco-Efficiency Integrated Methodology for Production Systems (ecoPROSYS) and the lean based resource efficiency assessment method, Multi-layer Stream Mapping (MSM). Thus, the framework assesses simultaneously the environmental, economic and efficiency performance of complex production systems, which helps to identify major inefficiencies and circumstances of low eco-efficiency performance, consequently leading to the definition of improvement priorities. Ultimately, this framework aims to facilitate the overall efficiency performance assessment, by an integrated multi-dimensional analysis, presented as the Total Efficiency Index. The logic behind this index is to combine, for each unit process and for the overall production process, two fundamental efficiency aspects, namely eco-efficiency and operations efficiency.

Abstract
The Multi-Layer Stream Mapping (MSM) methodology addresses current challenges regarding the applicability of Lean Thinking concepts in the domain of sustainability assessment tools. Therefore, MSM aims to assess the overall performance of a production system, while evaluating the productivity and efficiency of resource utilization as well as evaluate the costs related to missuses and inefficiencies and other process and domains variables. This paper highlights the benefits arising from the application of the MSM methodology in a real industrial case regarding the injection moulding process, namely fostering the quantification of the efficiency of different resources streams, for its improvement, for the several production processes involved. So, it is explained how MSM can contribute for a more sustainable production system with a continuously increasing productivity.

Abstract
While bottom-up approaches to object recognition are simple to design and implement, they do not yield the same performance as top-down approaches. On the other hand, it is not trivial to obtain a moderate number of plausible hypotheses to be efficiently verified by top-down approaches. To address these shortcomings, we propose a hybrid top-down bottom-up approach to object recognition where a bottom-up procedure that generates a set of hypothesis based on data is combined with a top-down process for evaluating those hypotheses. We use the recognition of rectangular cuboid shaped objects from 3D point cloud data as a benchmark problem for our research. Results obtained using this approach demonstrate promising recognition performances.

Abstract
Growing interest on business collaboration motivates today's industries, especially small and medium enterprises (SMEs) to establish and manage dynamic and non-hierarchical business networks to respond to market opportunities with added business benefits. This business environment requires concurrent work and real-time information sharing between key business partners in order to design and develop customised products. The use of traditional communication media such as e-mail, phone and fax is not satisfactory to get real-time information and is time-consuming and most often ineffective. In such environments, an Information and Communication Technology (ICT)/Web-based technology supports real-time information sharing among networked SMEs for the collaborative design and manufacturing of customised products. This study proposes an innovative ICT platform supporting SMEs collaboration, through Web and the Internet of Things technologies, which follows the Net-Challenge conceptual approach and methodological guidelines for SMEs to form and operate virtual organisations for the collaborative development and delivery of customised products. The ICT Platform was assessed in three different industry domains, namely the textile and apparel, the footwear and the machine tools, respectively. This ICT solution promotes collaboration, with substantial advantages for SMEs including the reduction of costs and delivery time and improvement of the innovation potential.